1 Executive Summary

  • The aim of this report is to …
  • The main discoveries are …



2 Full Report

2.1 Initial Data Analysis (IDA)

RStudio has many data sets already loaded in. The example below uses preloaded data direct from RStudio example dataset: mtcars.

Read about the mtcars data set.

In the rmd file, you will see how you can load your own dataset from either 1) an online source using a URL or 2) a local file on your own computer.

# LOAD DATA v1 - uncomment the link below to: load data direct from html
#cars = read.csv("dataset URL")

# LOAD DATA v2 - uncomment the link below to: load data from local file
#cars = read.csv("dataset file location")

# Quick look at top 5 rows of data
head(mtcars)
##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1
## Size of data
# For the mtcars dataset, there are 32 rows (the types of cars) and 11 variables (properties of the cars).
dim(mtcars)
## [1] 32 11
## R's classification of data
class(mtcars)
## [1] "data.frame"
## R's classification of variables
str(mtcars)
## 'data.frame':    32 obs. of  11 variables:
##  $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
##  $ disp: num  160 160 108 258 360 ...
##  $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
##  $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
##  $ qsec: num  16.5 17 18.6 19.4 17 ...
##  $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
##  $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
##  $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
##  $ carb: num  4 4 1 1 2 1 4 2 2 4 ...
#sapply(mtcars, class)

Summary:

  • The data came from …
  • The data is/is not valid because …
  • Possible issues include …
  • Each row represents …
  • Each column represents …


2.2 Research Question 1

Insert text and analysis.

Summary:

2.3 Research Question 2

Insert text and analysis.

Summary:

3 References

Style: APA


4 Beyond the Basics - extending your abilities with RMarkdown

This quick reference guide will cover some basic RMarkdown for use in your projects.


4.1 Lists

Here is a basic list:

  • To do 1

  • To do 2

  • To do 3


4.3 Tables

Here is a simple table.

Tables Are Cool
col 3 is right-aligned $1600
col 2 is centered $12
zebra stripes are neat $1


4.4 Images

Here is am image. It has not been adjusted in the rmd file, so represents the true size of the original image. This image is sourced directly from an online url.

To learn more about adding images directly from your own computer, see the comments in this rmd file.


Image source: https://petcube.com/blog/10-all-important-kitten-supplies-infographic/


4.5 Videos

Below you will find a video embedded into your RMarkdown file. Change the YouTube link in the rmd file to get a different video.


4.6 LaTeX

You can even use LaTeX in an RMarkdown document!

For example, how could you work out \(\sum_{i=1}^{5} x_{i}^3\)?


4.7 R Code

Here is an R code chunk:

Try the following commands in R.

1+ exp(3) + sin(0.5)
x=c(1,2,3)
x^2
sum(x)

Here is some in-line code in-line code. You can put any R code here for display, e.g. sum(x)


5 RMarkdown Resources

Check out the resources below for more information on RMarkdown.

How to use R Markdown

Mastering Markdown